Autonomously controlling a vehicle is a complex task that includes many different aspects. For example, the vehicle may plan a trajectory along a route to follow when operating autonomously. In general, the vehicle may use the planned trajectory to determine inputs for controlling the vehicle along the route. Therefore, the vehicle may include many different sensor systems to capture data about surroundings that are then used as inputs to compute the planned trajectory and control inputs. Additionally, the trajectory plan may be computed to a defined distance in front of the vehicle and then updated as the vehicle travels along the road and as operating conditions change (e.g., traffic, obstacles, etc.).
Moreover, as indicated, the trajectory plan is used by the vehicle as an input to determine how to control the vehicle at discrete instances in time. Thus, the vehicle uses an upcoming next portion of the trajectory plan as a target to compute controls for autonomously controlling the vehicle. However, the process of computing the trajectory plan can be computationally intensive. Therefore, latencies can be introduced into how the controls are computed if the vehicle updates the trajectory plan during or just after computing the controls. As a result, the vehicle may be operated with sudden movements due to the trajectory plan varying for a current segment of the road. Consequently, passengers may experience unexpected maneuvers that impact an overall ride experience.